Integration of relational and hierarchical network information for protein function prediction

BACKGROUND:In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO) database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions.RESULTS:We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing.CONCLUSION:A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor) and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased positive predictive value), and that this increase is consistent uniformly with GO-term depth. Additional in silico validation on a collection of new annotations recently added to GO confirms the advantages suggested by the cross-validation study. Taken as a whole, our results show that a hierarchical approach to network-based protein function prediction, that exploits the ontological structure of protein annotation databases in a principled manner, can offer substantial advantages over the successive application of 'flat' network-based methods.

Optimisation of chemoenzymatic processes in asymmetric synthesis

This thesis describes the optimisation of chemoenzymatic methods in asymmetric synthesis. Modern synthetic organic chemistry has experienced an enormous growth in biocatalytic methodologies; enzymatic transformations and whole cell bioconversions have become generally accepted synthetic tools for asymmetric synthesis. Biocatalysts are exceptional catalysts, combining broad substrate scope with high regio-, enantio- and chemoselectivities enabling the resolution of organic substrates with superb efficiency and selectivity. In this study three biocatalytic applications in enantioselective synthesis were explored and perhaps the most significant outcome of this work is the excellent enantioselectivity achieved through optimisation of reaction conditions improving the synthetic utility of the biotransformations. In the first chapter a summary of literature discussing the stereochemical control of baker’s yeast (Saccharomyces Cerevisae) mediated reduction of ketones by the introduction of sulfur moieties is presented, and sets the work of Chapter 2 in context. The focus of the second chapter was the synthesis and biocatalytic resolution of (±)-trans-2-benzenesulfonyl-3-n-butylcyclopentanone. For the first time the practical limitations of this resolution have been addressed providing synthetically useful quantities of enantiopure synthons for application in the total synthesis of both enantiomers of 4-methyloctanoic acid, the aggregation pheromone of the rhinoceros beetles of the genus Oryctes. The unique aspect of this enantioselective synthesis was the overall regio- and enantioselective introduction of the methyl group to the octanoic acid chain. This work is part of an ongoing research programme in our group focussed on baker’s yeast mediated kinetic resolution of 2-keto sulfones. The third chapter describes hydrolase-catalysed kinetic resolutions leading to a series of 3-aryl alkanoic acids. Hydrolysis of the ethyl esters with a series of hydrolases was undertaken to identify biocatalysts that yield the corresponding acids in highly enantioenriched form. Contrary to literature reports where a complete disappearance of efficiency and, accordingly enantioselection, was described upon kinetic resolution of sterically demanding 3-arylalkanoic acids, the highest reported enantiopurities of these acids was achieved (up to >98% ee) in this study through optimisation of reaction conditions. Steric and electronic effects on the efficiency and enantioselectivity of the biocatalytic transformation were also explored. Furthermore, a novel approach to determine the absolute stereochemistry of the enantiopure 3-aryl alkanoic acids was investigated through combination of co-crystallisation and X-ray diffraction linked with chiral HPLC analysis. The fourth chapter was focused on the development of a biocatalytic protocol for the asymmetric Henry reaction. Efficient kinetic resolution in hydrolase-mediated transesterification of cis- and trans- β-nitrocyclohexanol derivatives was achieved. Combination of a base-catalysed intramolecular Henry reaction coupled with the hydrolase-mediated kinetic resolution with the view to selective acetylation of a single stereoisomer was investigated. While dynamic kinetic resolution in the intramolecular Henry was not achieved, significant progress in each of the individual elements was made and significantly the feasibility of this process has been demonstrated. The final chapter contains the full experimental details, including spectroscopic and analytical data of all compounds synthesised in this project, while details of chiral HPLC analysis are included in the appendix. The data for the crystal structures are contained in the attached CD.

Ferrochelatase is a conserved downstream target of the blue light-sensing White collar complex in fungi.

Light is a universal signal perceived by organisms, including fungi, in which light regulates common and unique biological processes depending on the species. Previous research has established that conserved proteins, originally called White collar 1 and 2 from the ascomycete Neurospora crassa, regulate UV/blue light sensing. Homologous proteins function in distant relatives of N. crassa, including the basidiomycetes and zygomycetes, which diverged as long as a billion years ago. Here we conducted microarray experiments on the basidiomycete fungus Cryptococcus neoformans to identify light-regulated genes. Surprisingly, only a single gene was induced by light above the commonly used twofold threshold. This gene, HEM15, is predicted to encode a ferrochelatase that catalyses the final step in haem biosynthesis from highly photoreactive porphyrins. The C. neoformans gene complements a Saccharomyces cerevisiae hem15Delta strain and is essential for viability, and the Hem15 protein localizes to mitochondria, three lines of evidence that the gene encodes ferrochelatase. Regulation of HEM15 by light suggests a mechanism by which bwc1/bwc2 mutants are photosensitive and exhibit reduced virulence. We show that ferrochelatase is also light-regulated in a white collar-dependent fashion in N. crassa and the zygomycete Phycomyces blakesleeanus, indicating that ferrochelatase is an ancient target of photoregulation in the fungal kingdom.

Detecting separate time scales in genetic expression data.

BACKGROUND: Biological processes occur on a vast range of time scales, and many of them occur concurrently. As a result, system-wide measurements of gene expression have the potential to capture many of these processes simultaneously. The challenge however, is to separate these processes and time scales in the data. In many cases the number of processes and their time scales is unknown. This issue is particularly relevant to developmental biologists, who are interested in processes such as growth, segmentation and differentiation, which can all take place simultaneously, but on different time scales. RESULTS: We introduce a flexible and statistically rigorous method for detecting different time scales in time-series gene expression data, by identifying expression patterns that are temporally shifted between replicate datasets. We apply our approach to a Saccharomyces cerevisiae cell-cycle dataset and an Arabidopsis thaliana root developmental dataset. In both datasets our method successfully detects processes operating on several different time scales. Furthermore we show that many of these time scales can be associated with particular biological functions. CONCLUSIONS: The spatiotemporal modules identified by our method suggest the presence of multiple biological processes, acting at distinct time scales in both the Arabidopsis root and yeast. Using similar large-scale expression datasets, the identification of biological processes acting at multiple time scales in many organisms is now possible.

Conservation, duplication, and loss of the Tor signaling pathway in the fungal kingdom.

BACKGROUND: The nutrient-sensing Tor pathway governs cell growth and is conserved in nearly all eukaryotic organisms from unicellular yeasts to multicellular organisms, including humans. Tor is the target of the immunosuppressive drug rapamycin, which in complex with the prolyl isomerase FKBP12 inhibits Tor functions. Rapamycin is a gold standard drug for organ transplant recipients that was approved by the FDA in 1999 and is finding additional clinical indications as a chemotherapeutic and antiproliferative agent. Capitalizing on the plethora of recently sequenced genomes we have conducted comparative genomic studies to annotate the Tor pathway throughout the fungal kingdom and related unicellular opisthokonts, including Monosiga brevicollis, Salpingoeca rosetta, and Capsaspora owczarzaki. RESULTS: Interestingly, the Tor signaling cascade is absent in three microsporidian species with available genome sequences, the only known instance of a eukaryotic group lacking this conserved pathway. The microsporidia are obligate intracellular pathogens with highly reduced genomes, and we hypothesize that they lost the Tor pathway as they adapted and streamlined their genomes for intracellular growth in a nutrient-rich environment. Two TOR paralogs are present in several fungal species as a result of either a whole genome duplication or independent gene/segmental duplication events. One such event was identified in the amphibian pathogen Batrachochytrium dendrobatidis, a chytrid responsible for worldwide global amphibian declines and extinctions. CONCLUSIONS: The repeated independent duplications of the TOR gene in the fungal kingdom might reflect selective pressure acting upon this kinase that populates two proteinaceous complexes with different cellular roles. These comparative genomic analyses illustrate the evolutionary trajectory of a central nutrient-sensing cascade that enables diverse eukaryotic organisms to respond to their natural environments.

Modulation of heat shock transcription factor 1 as a therapeutic target for small molecule intervention in neurodegenerative disease.

Neurodegenerative diseases such as Huntington disease are devastating disorders with no therapeutic approaches to ameliorate the underlying protein misfolding defect inherent to poly-glutamine (polyQ) proteins. Given the mounting evidence that elevated levels of protein chaperones suppress polyQ protein misfolding, the master regulator of protein chaperone gene transcription, HSF1, is an attractive target for small molecule intervention. We describe a humanized yeast-based high-throughput screen to identify small molecule activators of human HSF1. This screen is insensitive to previously characterized activators of the heat shock response that have undesirable proteotoxic activity or that inhibit Hsp90, the central chaperone for cellular signaling and proliferation. A molecule identified in this screen, HSF1A, is structurally distinct from other characterized small molecule human HSF1 activators, activates HSF1 in mammalian and fly cells, elevates protein chaperone expression, ameliorates protein misfolding and cell death in polyQ-expressing neuronal precursor cells and protects against cytotoxicity in a fly model of polyQ-mediated neurodegeneration. In addition, we show that HSF1A interacts with components of the TRiC/CCT complex, suggesting a potentially novel regulatory role for this complex in modulating HSF1 activity. These studies describe a novel approach for the identification of new classes of pharmacological interventions for protein misfolding that underlies devastating neurodegenerative disease.

Environmental and genetic determinants of colony morphology in yeast.

Nutrient stresses trigger a variety of developmental switches in the budding yeast Saccharomyces cerevisiae. One of the least understood of such responses is the development of complex colony morphology, characterized by intricate, organized, and strain-specific patterns of colony growth and architecture. The genetic bases of this phenotype and the key environmental signals involved in its induction have heretofore remained poorly understood. By surveying multiple strain backgrounds and a large number of growth conditions, we show that limitation for fermentable carbon sources coupled with a rich nitrogen source is the primary trigger for the colony morphology response in budding yeast. Using knockout mutants and transposon-mediated mutagenesis, we demonstrate that two key signaling networks regulating this response are the filamentous growth MAP kinase cascade and the Ras-cAMP-PKA pathway. We further show synergistic epistasis between Rim15, a kinase involved in integration of nutrient signals, and other genes in these pathways. Ploidy, mating-type, and genotype-by-environment interactions also appear to play a role in the controlling colony morphology. Our study highlights the high degree of network reuse in this model eukaryote; yeast use the same core signaling pathways in multiple contexts to integrate information about environmental and physiological states and generate diverse developmental outputs.

Yeast screens identify the RNA polymerase II CTD and SPT5 as relevant targets of BRCA1 interaction.

BRCA1 has been implicated in numerous DNA repair pathways that maintain genome integrity, however the function responsible for its tumor suppressor activity in breast cancer remains obscure. To identify the most highly conserved of the many BRCA1 functions, we screened the evolutionarily distant eukaryote Saccharomyces cerevisiae for mutants that suppressed the G1 checkpoint arrest and lethality induced following heterologous BRCA1 expression. A genome-wide screen in the diploid deletion collection combined with a screen of ionizing radiation sensitive gene deletions identified mutants that permit growth in the presence of BRCA1. These genes delineate a metabolic mRNA pathway that temporally links transcription elongation (SPT4, SPT5, CTK1, DEF1) to nucleopore-mediated mRNA export (ASM4, MLP1, MLP2, NUP2, NUP53, NUP120, NUP133, NUP170, NUP188, POM34) and cytoplasmic mRNA decay at P-bodies (CCR4, DHH1). Strikingly, BRCA1 interacted with the phosphorylated RNA polymerase II (RNAPII) carboxy terminal domain (P-CTD), phosphorylated in the pattern specified by the CTDK-I kinase, to induce DEF1-dependent cleavage and accumulation of a RNAPII fragment containing the P-CTD. Significantly, breast cancer associated BRCT domain defects in BRCA1 that suppressed P-CTD cleavage and lethality in yeast also suppressed the physical interaction of BRCA1 with human SPT5 in breast epithelial cells, thus confirming SPT5 as a relevant target of BRCA1 interaction. Furthermore, enhanced P-CTD cleavage was observed in both yeast and human breast cells following UV-irradiation indicating a conserved eukaryotic damage response. Moreover, P-CTD cleavage in breast epithelial cells was BRCA1-dependent since damage-induced P-CTD cleavage was only observed in the mutant BRCA1 cell line HCC1937 following ectopic expression of wild type BRCA1. Finally, BRCA1, SPT5 and hyperphosphorylated RPB1 form a complex that was rapidly degraded following MMS treatment in wild type but not BRCA1 mutant breast cells. These results extend the mechanistic links between BRCA1 and transcriptional consequences in response to DNA damage and suggest an important role for RNAPII P-CTD cleavage in BRCA1-mediated cancer suppression.

The prevalence and regulation of antisense transcripts in Schizosaccharomyces pombe.

A strand-specific transcriptome sequencing strategy, directional ligation sequencing or DeLi-seq, was employed to profile antisense transcriptome of Schizosaccharomyces pombe. Under both normal and heat shock conditions, we found that polyadenylated antisense transcripts are broadly expressed while distinct expression patterns were observed for protein-coding and non-coding loci. Dominant antisense expression is enriched in protein-coding genes involved in meiosis or stress response pathways. Detailed analyses further suggest that antisense transcripts are independently regulated with respect to their sense transcripts, and diverse mechanisms might be potentially involved in the biogenesis and degradation of antisense RNAs. Taken together, antisense transcription may have profound impacts on global gene regulation in S. pombe.

PKC signaling regulates drug resistance of the fungal pathogen Candida albicans via circuitry comprised of Mkc1, calcineurin, and Hsp90.

Fungal pathogens exploit diverse mechanisms to survive exposure to antifungal drugs. This poses concern given the limited number of clinically useful antifungals and the growing population of immunocompromised individuals vulnerable to life-threatening fungal infection. To identify molecules that abrogate resistance to the most widely deployed class of antifungals, the azoles, we conducted a screen of 1,280 pharmacologically active compounds. Three out of seven hits that abolished azole resistance of a resistant mutant of the model yeast Saccharomyces cerevisiae and a clinical isolate of the leading human fungal pathogen Candida albicans were inhibitors of protein kinase C (PKC), which regulates cell wall integrity during growth, morphogenesis, and response to cell wall stress. Pharmacological or genetic impairment of Pkc1 conferred hypersensitivity to multiple drugs that target synthesis of the key cell membrane sterol ergosterol, including azoles, allylamines, and morpholines. Pkc1 enabled survival of cell membrane stress at least in part via the mitogen activated protein kinase (MAPK) cascade in both species, though through distinct downstream effectors. Strikingly, inhibition of Pkc1 phenocopied inhibition of the molecular chaperone Hsp90 or its client protein calcineurin. PKC signaling was required for calcineurin activation in response to drug exposure in S. cerevisiae. In contrast, Pkc1 and calcineurin independently regulate drug resistance via a common target in C. albicans. We identified an additional level of regulatory control in the C. albicans circuitry linking PKC signaling, Hsp90, and calcineurin as genetic reduction of Hsp90 led to depletion of the terminal MAPK, Mkc1. Deletion of C. albicans PKC1 rendered fungistatic ergosterol biosynthesis inhibitors fungicidal and attenuated virulence in a murine model of systemic candidiasis. This work establishes a new role for PKC signaling in drug resistance, novel circuitry through which Hsp90 regulates drug resistance, and that targeting stress response signaling provides a promising strategy for treating life-threatening fungal infections.

Chromatin: bind at your own RSC.

Recent work has identified a novel RSC-nucleosome complex that both strongly phases flanking nucleosomes and presents regulatory sites for ready access. These results challenge several widely held views.

Measuring fast gene dynamics in single cells with time-lapse luminescence microscopy.

Time-lapse fluorescence microscopy is an important tool for measuring in vivo gene dynamics in single cells. However, fluorescent proteins are limited by slow chromophore maturation times and the cellular autofluorescence or phototoxicity that arises from light excitation. An alternative is luciferase, an enzyme that emits photons and is active upon folding. The photon flux per luciferase is significantly lower than that for fluorescent proteins. Thus time-lapse luminescence microscopy has been successfully used to track gene dynamics only in larger organisms and for slower processes, for which more total photons can be collected in one exposure. Here we tested green, yellow, and red beetle luciferases and optimized substrate conditions for in vivo luminescence. By combining time-lapse luminescence microscopy with a microfluidic device, we tracked the dynamics of cell cycle genes in single yeast with subminute exposure times over many generations. Our method was faster and in cells with much smaller volumes than previous work. Fluorescence of an optimized reporter (Venus) lagged luminescence by 15-20 min, which is consistent with its known rate of chromophore maturation in yeast. Our work demonstrates that luciferases are better than fluorescent proteins at faithfully tracking the underlying gene expression.

Different Mechanisms Confer Gradual Control and Memory at Nutrient- and Stress-Regulated Genes in Yeast.

Cells respond to environmental stimuli by fine-tuned regulation of gene expression. Here we investigated the dose-dependent modulation of gene expression at high temporal resolution in response to nutrient and stress signals in yeast. The GAL1 activity in cell populations is modulated in a well-defined range of galactose concentrations, correlating with a dynamic change of histone remodeling and RNA polymerase II (RNAPII) association. This behavior is the result of a heterogeneous induction delay caused by decreasing inducer concentrations across the population. Chromatin remodeling appears to be the basis for the dynamic GAL1 expression, because mutants with impaired histone dynamics show severely truncated dose-response profiles. In contrast, the GRE2 promoter operates like a rapid off/on switch in response to increasing osmotic stress, with almost constant expression rates and exclusively temporal regulation of histone remodeling and RNAPII occupancy. The Gal3 inducer and the Hog1 mitogen-activated protein (MAP) kinase seem to determine the different dose-response strategies at the two promoters. Accordingly, GAL1 becomes highly sensitive and dose independent if previously stimulated because of residual Gal3 levels, whereas GRE2 expression diminishes upon repeated stimulation due to acquired stress resistance. Our analysis reveals important differences in the way dynamic signals create dose-sensitive gene expression outputs.

Amino acid permeases require COPII components and the ER resident membrane protein Shr3p for packaging into transport vesicles in vitro.

In S. cerevisiae lacking SHR3, amino acid permeases specifically accumulate in membranes of the endoplasmic reticulum (ER) and fail to be transported to the plasma membrane. We examined the requirements of transport of the permeases from the ER to the Golgi in vitro. Addition of soluble COPII components (Sec23/24p, Sec13/31p, and Sar1p) to yeast membrane preparations generated vesicles containing the general amino acid permease. Gap1p, and the histidine permease, Hip1p. Shr3p was required for the packaging of Gap1p and Hip1p but was not itself incorporated into transport vesicles. In contrast, the packaging of the plasma membrane ATPase, Pma1p, and the soluble yeast pheromone precursor, glycosylated pro alpha factor, was independent of Shr3p. In addition, we show that integral membrane and soluble cargo colocalize in transport vesicles, indicating that different types of cargo are not segregated at an early step in secretion. Our data suggest that specific ancillary proteins in the ER membrane recruit subsets of integral membrane protein cargo into COPII transport vesicles.

Selection of yeast strains for bioethanol production from UK seaweeds

Macroalgae (seaweeds) are a promising feedstock for the production of third generation bioethanol, since they have high carbohydrate contents, contain little or no lignin and are available in abundance. However, seaweeds typically contain a more diverse array of monomeric sugars than are commonly present in feedstocks derived from lignocellulosic material which are currently used for bioethanol production. Hence, identification of a suitable fermentative microorganism that can utilise the principal sugars released from the hydrolysis of macroalgae remains a major objective. The present study used a phenotypic microarray technique to screen 24 different yeast strains for their ability to metabolise individual monosaccharides commonly found in seaweeds, as well as hydrolysates following an acid pre-treatment of five native UK seaweed species (Laminaria digitata, Fucus serratus, Chondrus crispus, Palmaria palmata and Ulva lactuca). Five strains of yeast (three Saccharomyces spp, one Pichia sp and one Candida sp) were selected and subsequently evaluated for bioethanol production during fermentation of the hydrolysates. Four out of the five selected strains converted these monomeric sugars into bioethanol, with the highest ethanol yield (13 g L−1) resulting from a fermentation using C. crispus hydrolysate with Saccharomyces cerevisiae YPS128. This study demonstrated the novel application of a phenotypic microarray technique to screen for yeast capable of metabolising sugars present in seaweed hydrolysates; however, metabolic activity did not always imply fermentative production of ethanol.